




from ...configuration_utils import PretrainedConfig







class     A(		UpperCamelCase  ):



 '''simple docstring'''


 UpperCamelCase		  =		'''bert-generation'''

 def __init__(							self   :    Any		,				A_   :    List[str]=50358		,				A_   :    str=1024		,				A_   :    Any=24		,				A_   :    str=16		,				A_   :    Optional[int]=4096		,				A_   :    Any="gelu"		,				A_   :    Tuple=0.1		,				A_   :    List[Any]=0.1		,				A_   :    Optional[Any]=512		,				A_   :    List[Any]=0.02		,				A_   :    List[str]=1E-12		,				A_   :    Any=0		,				A_   :    Tuple=2		,				A_   :    Union[str, Any]=1		,				A_   :    Optional[Any]="absolute"		,				A_   :    Optional[Any]=True		,				**A_   :    List[Any]		,				)  ->      Optional[Any]:

       """simple docstring"""






       super().__init__(pad_token_id=A_		,				bos_token_id=A_		,				eos_token_id=A_		,				**A_    )

       lowerCamelCase_							=       vocab_size
       lowerCamelCase_							=       hidden_size
       lowerCamelCase_							=       num_hidden_layers
       lowerCamelCase_							=       num_attention_heads
       lowerCamelCase_							=       hidden_act
       lowerCamelCase_							=       intermediate_size
       lowerCamelCase_							=       hidden_dropout_prob
       lowerCamelCase_							=       attention_probs_dropout_prob
       lowerCamelCase_							=       max_position_embeddings
       lowerCamelCase_							=       initializer_range
       lowerCamelCase_							=       layer_norm_eps
       lowerCamelCase_							=       position_embedding_type
       lowerCamelCase_							=       use_cache











"""simple docstring"""





from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow

from ..bert.test_tokenization_bert import BertTokenizationTest






@require_tokenizers
class 	a		(   __snake_case						):
    SCREAMING_SNAKE_CASE		:	Optional[Any]		=					DistilBertTokenizer
    SCREAMING_SNAKE_CASE		:	Optional[Any]		=					DistilBertTokenizerFast
    SCREAMING_SNAKE_CASE		:	int		=					True






    @slow
    def   UpperCamelCase			(			self	:				Optional[int]   )	->						int:
      lowerCamelCase_       	=		DistilBertTokenizer.from_pretrained('distilbert-base-uncased'   )

      lowerCamelCase_       	=		tokenizer.encode('sequence builders'			,		add_special_tokens=__SCREAMING_SNAKE_CASE   )
      lowerCamelCase_       	=		tokenizer.encode('multi-sequence build'			,		add_special_tokens=__SCREAMING_SNAKE_CASE   )

      lowerCamelCase_       	=		tokenizer.build_inputs_with_special_tokens(__SCREAMING_SNAKE_CASE   )
      lowerCamelCase_       	=		tokenizer.build_inputs_with_special_tokens(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   )

      assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
      assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [
          tokenizer.sep_token_id
      ]




